Is it Useful to Learn Python Language for Big Data?

October 24, 2017

If you are a big data enthusiast and want to enter the field of big data, or if you are employing a development team to handle your big data requirements, you would find yourself pondering over this question many times. Is Python the best choice over the many other programming languages available? Which language should you train yourself or your staff in? Python or R or Hadoop? well, an article cannot solve your quandary, but read on if you need to find out what Python has to offer.

Python is an open source programing language, which is most popularly used in big data. Python Language is synonymous with flexibility, powerful yet easy to use features. Python has its USP in the rich set of utilities and the libraries it offers for analytics and data processing tasks. So, all in all, it is a given fact that among other options available Python maintains its popularity essentially because of it’s easy to use features, which supports big data processing.

Python was developed with the philosophy to bring coding to an open platform, where coding becomes easy, more readable, where one can write less number of lines and yet get the desired results. Keeping the objective in mind, a standard library was introduced, which contained ready to use tools for performing various tasks.

These features make Python the most preferred choice for software development, and mostly so for Artificial intelligence and Machine Learning.

It offers a speedy learning curve and reduced development time, the syntax in Python is much cleaner and neater in comparison to other languages. It is easy to debug due to shorter codes. The modular architecture makes it easy to merely import and use a module rather than writing a large block of code. Great choice for beginners. Shorter and quicker codes reduce the development time drastically.

You can automate the repetitive tasks, for lesser cognitively demanding tasks, tasks that need little decision making can be automatically programmed by writing a script in Python.

It is the most common choice for data scientist and analytics because of the convenience of feature-rich modules in Python which makes it easy to conduct data analytics in an efficient manner.

Python is an object-oriented language, so if you learn Python it will make it easy for you to switch to any other object-oriented language. You will only need to learn the syntax of the other language.

It is the future for Artificial Intelligence and Machine Learning, which will be integrated in most functions in the very near future. Python becomes the premium choice for Machine learning algorithms mainly because of the portable extendable and scalable features of the language.

The field of data science and analytics, more specifically artificial intelligence and machine learning will only continue to flourish in the coming years. If you are looking to take a plunge in this field, then fluency in Python can be considered a prerequisite. Learning Python has minimal investment and maximum benefits, it then surely becomes an advantage to learn.